{
  "abstract": "Background\n\nNonarteritic anterior ischaemic optic neuropathy (NAION) is an acute optic neuropathy characterized primarily by sudden vision loss accompanied by visual field defects. Early screening and diagnosis are especially critical because of the diagnostic challenges associated with the initial stages of NAION and its irreversible nature. This study proposes a multimodal diagnostic approach that integrates optical coherence tomography angiography (OCTA) and radiomics for the identification of high-risk NAION populations and for distinguishing its acute phase.Methods\n\nWithout requiring region-of-interest (ROI) delineation, we globally extracted radiomics features from OCTA images and combined them with clinical information. Multilayer perceptron (MLP) models were subsequently developed for three distinct scenarios: single-modality single-region, multimodality single-region, and multimodality multiregion analyses.Results\n\nThe results demonstrate that the multimodality multiregion model, incorporating multiregional OCTA features and clinical information, achieved optimal performance in NAION prediction, with an AUC of 0.996 (95% CI, 0.983-1.000) and an ACC of 0.970. This model also exhibited outstanding performance in differentiating acute-phase NAION from acute-phase optic neuritis (ON), with an AUC of 0.989 (95% CI, 0.966-1.000) and an ACC of 0.944.Conclusions\n\nBy integrating multisource information, the model not only enhances diagnostic accuracy but also provides clinicians with comprehensive decision support perspectives. This advancement facilitates early intervention and personalized treatment strategies, thereby mitigating disease progression and improving prognostic outcomes for NAION patients. This study establishes a novel diagnostic pathway and offers innovative methodologies for the early diagnosis and management of NAION.",
  "abstract_shown": true,
  "affiliations": [
    "First Affiliated Hospital of Kunming Medical University, Department of Ophthalmology, Kunming, China.",
    "Department of Ophthalmology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.",
    "School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China.",
    "School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China. jfenghe@kust.edu.cn.",
    "First Affiliated Hospital of Kunming Medical University, Department of Ophthalmology, Kunming, China. maniujia@163.com."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Peixian Yang"
    },
    {
      "affs": [
        2
      ],
      "name": "Songlin Cui"
    },
    {
      "affs": [
        0
      ],
      "name": "Yuxin Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "Ruijuan Zhao"
    },
    {
      "affs": [
        0
      ],
      "name": "Xiaoting Xi"
    },
    {
      "affs": [
        2
      ],
      "name": "Xin Xiong"
    },
    {
      "affs": [
        2
      ],
      "name": "Luda Chen"
    },
    {
      "affs": [
        3
      ],
      "name": "Jianfeng He"
    },
    {
      "affs": [
        4
      ],
      "name": "Jia Ma"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fa51phm1pmc9m.bib",
  "cited_by": 0,
  "doi": "10.1186/s12886-026-05186-w",
  "fulltext_url": "https://europepmc.org/articles/PMC13721393",
  "id": "fa51phm1pmc9m",
  "issns": [
    "1471-2415"
  ],
  "landing_url": "https://europepmc.org/article/MED/42958118",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Research"
    ],
    [
      "openalex",
      "2741|Radiomics and Machine Learning in Medical Imaging"
    ]
  ],
  "openalex": "W7172292440",
  "pdf_url": "https://europepmc.org/articles/PMC13721393?pdf=render",
  "pmcid": "PMC13721393",
  "pmid": "42958118",
  "published": "2026-08-03",
  "publisher": "BMC",
  "ris": "https://research.draconitic.com/paper/fa51phm1pmc9m.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T00:20:47Z",
      "native_id": "MED:42958118",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42958118"
    },
    {
      "first_seen": "2026-11-03T12:22:05Z",
      "native_id": "PMC13721393",
      "source": "pmc",
      "url": "https://doi.org/10.1186/s12886-026-05186-w"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Radiomics and Machine Learning in Medical Imaging",
      "subfield": "imaging"
    }
  ],
  "title": "Application of a multimodal model integrating optical coherence tomography angiography (OCTA) and radiomics for the identification of high-risk Nonarteritic anterior ischaemic optic neuropathy (NAION) populations and for distinguishing its acute phase.",
  "title_text": "Application of a multimodal model integrating optical coherence tomography angiography (OCTA) and radiomics for the identification of high-risk Nonarteritic anterior ischaemic optic neuropathy (NAION) populations and for distinguishing its acute phase.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-03T12:22:05Z",
  "url": "https://research.draconitic.com/paper/fa51phm1pmc9m",
  "venue": "BMC ophthalmology",
  "versions": []
}